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Movement

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Concurrent validity and test reliability of the deep learning markerless motion capture system during the overhead squat.

Scientific reports
Marker-based optical motion capture systems have been used as a cardinal vehicle to probe and understand the underpinning mechanism of human posture and movement, but it is time-consuming for complex and delicate data acquisition and analysis, labor-...

An Emotion Recognition Method for Humanoid Robot Body Movements Based on a PSO-BP-RMSProp Neural Network.

Sensors (Basel, Switzerland)
This paper mainly explores the computational model that connects a robot's emotional body movements with human emotion to propose an emotion recognition method for humanoid robot body movements. There is sparse research directly carried out from this...

Human motion recognition based on feature fusion and residual networks.

Scientific reports
Addressing the issue of low recognition accuracy in human motion detection when relying on a single feature, a novel approach integrating Frequency Modulated Continuous Wave (FMCW) radar technology with a Residual Network (ResNet) architecture has be...

Deep learning methods for 3D magnetic resonance image denoising, bias field and motion artifact correction: a comprehensive review.

Physics in medicine and biology
Magnetic resonance imaging (MRI) provides detailed structural information of the internal body organs and soft tissue regions of a patient in clinical diagnosis for disease detection, localization, and progress monitoring. MRI scanner hardware manufa...

Human-in-the-Loop Modeling and Bilateral Skill Transfer Control of Soft Exoskeleton.

Sensors (Basel, Switzerland)
Soft exoskeletons (exosuits) are expected to provide a comfortable wearing experience and compliant assistance compared with traditional rigid exoskeleton robots. In this paper, an exosuit with twisted string actuators (TSAs) is developed to provide ...

Identifying Infant Body Position from Inertial Sensors with Machine Learning: Which Parameters Matter?

Sensors (Basel, Switzerland)
The efficient classification of body position is crucial for monitoring infants' motor development. It may fast-track the early detection of developmental issues related not only to the acquisition of motor milestones but also to postural stability a...

Enhancing artificial intelligence-driven sleep apnea diagnosis: The critical importance of input signal proficiency with a focus on mandibular jaw movements.

Journal of prosthodontics : official journal of the American College of Prosthodontists
PURPOSE: This review aims to highlight the pivotal role of the mandibular jaw movement (MJM) signal in advancing artificial intelligence (AI)-powered technologies for diagnosing obstructive sleep apnea (OSA).

Using deep learning to classify developmental differences in reaching and placing movements in children with and without autism spectrum disorder.

Scientific reports
Autism Spectrum Disorder (ASD) is among the most prevalent neurodevelopmental disorders, yet the current diagnostic procedures rely on behavioral analyses and interviews, without objective screening methods to support the diagnostic process. This stu...

Real-time 3D MR guided radiation therapy through orthogonal MR imaging and manifold learning.

Medical physics
BACKGROUND: In magnetic resonance image (MRI)-guided radiotherapy (MRgRT), 2D rapid imaging is commonly used to track moving targets with high temporal frequency to minimize gating latency. However, anatomical motion is not constrained to 2D, and a p...

Fast motion-compensated reconstruction for 4D-CBCT using deep learning-based groupwise registration.

Biomedical physics & engineering express
. Previous work has that deep learning (DL)-enhanced 4D cone beam computed tomography (4D-CBCT) images improve motion modeling and subsequent motion-compensated (MoCo) reconstruction for 4D-CBCT. However, building the motion model at treatment time v...